A Lifespan-Generalizable Skull-Stripping Model for Brain MRI

dGAMLSS enables exact population brain chart model fitting across multiple institutions without sharing patient-level data, removing the privacy barrier to federated multi-site clinical deployment of brain charting

TissUnet extends quantitative MRI analysis beyond the brain, segmenting skull bone, subcutaneous fat, and muscle from routine T1-weighted scans across all ages and pathologies, achieving an 89% acceptance rate in healthy and brain tumor cohorts.

Brain growth charts reveal dynamic extra-axial CSF trajectories in clinical pediatric MRI, enabling automated macrocephaly diagnosis and challenging fixed-measurement guidelines.